The survey of family history of diabetes in patients with type 2 diabetes in Chaharmahal va Bakhteyari province, Iran, 2008

چکیده: زمینه و هدف: دیابت از گروه بیماری های متابولیک و یک اختلال چند عاملی است که با افزایش مزمن قند خون مشخص می شود. از آنجایی که در زمینه اپیدمیولوژی ژنتیک دیابت نوع 2 در کشور ما، مطالعات اندکی انجام شده و هنوز بطور قطعی مشخص نیست که توارث دیابت نوع 2 بیشتر از طرف کدام یک از والدین (پدر یا مادر) به فرزندان منتقل می شود، این مطالعه با هدف بررسی زمینه ژنتیکی بیماران دیابتی نوع 2 استان چهارمحال و بختیاری طراحی و اجرا گردید. روش بررسی: این بررسی یک مطالعه اپیدمیولوژیک از نوع توصیفی-تحلیلی است که جامعه پژوهش آن افراد مبتلا به دیابت نوع 2 در استان چهارمحال و بختیاری در سال 1387 بود. تعداد 254 نفر به روش تصادفی دو مرحله ای انتخاب و مورد بررسی قرار گرفتند. داده ها بوسیله مصاحبه و با تکمیل فرمی، جمع آوری و با نرم افزار STATA9 و آزمون مجذور کا مورد تجزیه و تحلیل قرار گرفت. یافته ها: از254 نفر بررسی شده 150 نفر (59) مونث و 104 نفر(41) مذکر بودند. متوسط سن آنها 6/8±8/54 سال و متوسط مدت زمان ابتلا به دیابت در آنها 8/5±4/7 سال بود. 116 نفر (7/45) از آنها دارای سابقه خانوادگی مثبت دیابت بودند که از این میان، 4/61 مادر دیابتی، 8/19 پدر دیابتی، 9/62 خواهر دیابتی، 1/18 برادر دیابتی، 5/40 دختر دیابتی و 1/18 پسر دیابتی داشتند. سابقه خانوادگی دیابت در مادر بیشتر از پدر، در خواهر بیشتر از برادر و در دختران بیشتر از پسران بود (001/0>P). نتیجه گیری: نسبت شانس ابتلا به دیابت برای کسانی که سابقه خانوادگی مثبت دیابت در مادر دارند بیشتر و مهم تر از پدر بوده و می توان اظهار نمود که به احتمال قوی، توارث دیابت نوع 2 بیشتر از طریق مادر به فرزندان منتقل می شود.

Simulation of Leaching of Starch from Potato in a Batch Extractor

Abstrac

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy

Phylogenetic relationships of Iranian Infectious Pancreatic Necrosis Virus (IPNV) based on deduced amino acid sequences of genome segment A and B cDNA

Infectious Pancreatic Necrosis Virus (IPNV) is the causal agent of a highly contagious disease that affects many species of fish and shellfish. This virus causes economically important diseases of farmed rainbow trout, Oncorhynchus mykiss, in Iran which is often associated with the transmission of pathogens from European resources. In this study, moribund rainbow trout fry were collected during an outbreak of IPNV in three different fish farms in one northern province (Mazandaran), and two west provinces (Chaharmahal and Bakhtiari, and Kohgiluyeh and Boyer Ahmad) of Iran. We investigated full genome sequence of Iranian IPNV and compared it with previously identified IPNV sequences. The sequences of different structural and non-structural protein genes were compared with other aquatic birnaviruses sequenced to date. Our results showed that the Iranian isolate fall within genogroup 5, serotype A2 strain SP, having 99 % identity with the strain 1146 from Spain. These results suggest that the Iranian isolate may have originated from Europe

Green synthesis of iron nanoparticles using Pistacia-atlantica leaf extract for enhanced removal of Cr(VI) from aqueous solution

The discharge of chromium-containing wastewater from various industries into aqueous environments is regarded as an important and challengeable matter due to its high toxicity. The application of conventional methods for eliminating this pollutant are often very expensive and difficult. Therefore, the adsorption process has been introduced as a desirable and effective method for removing chromium ions from aqueous media. In this research, iron nanoparticles (Fe-NPs) were synthesized using Pistacia-atlantica leaf extract as a reducing agent, then they were characterized by DLS, XRD, FT-IR, FESEM/EDS, and TEM techniques and its effectiveness to eliminate hexavalent chromium (Cr (VI)) from aqueous solutions was carried out. The capability of the batch adsorption procedure was assessed under different operational factors, such as initial pH, adsorbent dose and initial Cr (VI) concentration. Optimum adsorption conditions were determined at initial pH of 2, Cr (VI) concentration of 25 mg Lˉ¹ and adsorbent dose of 0.24 g Lˉ¹. Based on the obtained results, the highest removal efficiency (99.9%) by the adsorption process was occurred at pH of 2, concentration of 5 mg Lˉ¹ and 30 min of operational time. On the other hand, the results showed that the percentage of the pollutant elevated by increasing the contact time and amount of adsorbent dose, whereas that of was declined by increasing the initial concentration of Cr (VI). Besides, the experimental equilibrium data was evaluated by Langmuir, Freundlich, and Temkin isotherm models, and the outcomes revealed conformity with the Langmuir isotherm model. The Cr (VI) adsorption utilizing Fe-NPs adhered to a pseudo-first-order kinetic model. Eventually, thermodynamic studies demonstrated that the adsorption of Cr (VI) onto the surface of the Fe-NPs is endothermic and spontaneous

Development of the Nebraska Department of Transportation Winter Severity Index

Adverse weather conditions are responsible for millions of vehicular crashes, thousands of vehicular deaths and billions of dollars in economic and congestion costs. Many transportation agencies utilize a performance or mobility metric to assess how well they are maintaining road access. This research focuses on the development of a winter severity index for the State of Nebraska (NEWINS). NEWINS is an event-driven index that was derived for the Nebraska Department of Transportation (NDOT) and its districts across the state. The NEWINS framework includes a categorical storm classification framework and climatological aspect to capture atmospheric conditions more accurately across the diverse spatial regions of Nebraska. A ten-year (2006-2016) winter season database of meteorological variables for Nebraska was obtained from the National Centers for Environmental Information. Meteorological parameters were grouped into categories that subsequently provided a storm classification database. The NEWINS is based on a weighted linear combination to the collected database to measure severity statewide and across NDOT individual districts. The NEWINS results were compared to other meteorological variables, many used in other agencies’ winter severity indices. This comparison verified the NEWINS robustness for the observed events for the ten year period. For example, an assessment of the difference between days with observed snowfall versus days with accumulated snowfall revealed a 39% average reduction in days. Furthermore, the NEWINS results highlight the greater number of events during the 2009-2010 winter season, and the lack of events during the 2011-2012 drought year. The NEWINS also shows strong differences monthly and among NDOT districts across the state with a general decrease in events from the western to eastern NDOT districts. In addition, NEWINS storm classifications were compared to NDOT winter maintenance operations performance data for a sample winter season. Last, the 2016-17 winter season was computed to provide a testbed for the NEWINS procedure. It is expected that the NEWINS could help transportation personnel to efficiently allocate resources during adverse weather events, while balancing safety, mobility, and available budget. Further, the theoretical and practical contributions provided by the NEWINS can be used by other agencies to assess their weather sensitivity

Development of the Nebraska Department of Transportation Winter Severity Index

Adverse weather conditions are responsible for millions of vehicular crashes, thousands of vehicular deaths and billions of dollars in economic and congestion costs. Many transportation agencies utilize a performance or mobility metric to assess how well they are maintaining road access. This research focuses on the development of a winter severity index for the State of Nebraska (NEWINS). NEWINS is an event-driven index that was derived for the Nebraska Department of Transportation (NDOT) and its districts across the state. The NEWINS framework includes a categorical storm classification framework and climatological aspect to capture atmospheric conditions more accurately across the diverse spatial regions of Nebraska. A ten-year (2006-2016) winter season database of meteorological variables for Nebraska was obtained from the National Centers for Environmental Information. Meteorological parameters were grouped into categories that subsequently provided a storm classification database. The NEWINS is based on a weighted linear combination to the collected database to measure severity statewide and across NDOT individual districts. The NEWINS results were compared to other meteorological variables, many used in other agencies’ winter severity indices. This comparison verified the NEWINS robustness for the observed events for the ten year period. For example, an assessment of the difference between days with observed snowfall versus days with accumulated snowfall revealed a 39% average reduction in days. Furthermore, the NEWINS results highlight the greater number of events during the 2009-2010 winter season, and the lack of events during the 2011-2012 drought year. The NEWINS also shows strong differences monthly and among NDOT districts across the state with a general decrease in events from the western to eastern NDOT districts. In addition, NEWINS storm classifications were compared to NDOT winter maintenance operations performance data for a sample winter season. Last, the 2016-17 winter season was computed to provide a testbed for the NEWINS procedure. It is expected that the NEWINS could help transportation personnel to efficiently allocate resources during adverse weather events, while balancing safety, mobility, and available budget. Further, the theoretical and practical contributions provided by the NEWINS can be used by other agencies to assess their weather sensitivity

Psychometric evaluation of the postpartum specific anxiety scale in an Iranian population (PSAS-IR)

Background: Anxiety is one of the most prevalent mental health disorders among mothers during the postpartum period, which can lead to maternal and infant physical and psychological consequences. The Postpartum Specific Anxiety Scale (PSAS) predicts unique variance in postnatal outcomes over and above general anxiety tools. It has never been used in Iran and its validity and reliability have not been assessed either. Therefore, the present study aimed to translate and investigate the psychometric properties of the PSAS-IR. Methods: 510 women, from six weeks to six months postpartum, were selected through random sampling in 2020. After forward and back-translation, the face validity, content validity, and construct validity of PSAS (through confirmatory factor analysis) were examined. The reliability of the scale was assessed using both internal consistency (Cronbach’s alpha) and test-retest stability methods. Results: CVI and CVR values of the PSAS tool were 0.89 and 0.88, respectively. The good fit indices confirmed the validity of four-factor structure. Cronbach’s alpha coefficient and Intra Correlation Coefficient (ICC) equaled 0.93 and 0.92, respectively. Conclusion: The Persian version of PSAS is a valid and reliable four-factor scale, it will improve the measurement of postpartum anxiety in an Iranian setting. This will improve the measurement of postpartum anxiety in an Iranian setting